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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Cosmological dynamics of string theory axion strings

The quantum chromodynamics (QCD) axion may solve the strong CP problem and explain the dark matter (DM) abundance of our Universe. The axion was originally proposed to arise as the pseudo-Nambu-Goldstone boson of global U⁢(1) PQ Peccei-Quinn (PQ) symmetry breaking, but axions also arise generically in string theory as zero modes of higher-dimensional gauge fields. In this work we show that string theory axions behave fundamentally differently from field theory axions in the early Universe. Field theory axions may form axion strings if the PQ phase transition takes place after inflation. In contrast, we show that string theory axions do not generically form axion strings. In special inflationary paradigms, such as D-brane inflation, string theory axion strings may form; however, their tension is parametrically larger than that of field theory axion strings. We then show that such QCD axion strings overproduce the DM abundance for all allowed QCD axion masses and are thus ruled out, except in scenarios with large warping. A loop-hole to this conclusion arises in the axiverse, where an axion string could be composed of multiple different axion mass eigenstates; a heavier eigenstate could collapse the network earlier, allowing for the QCD axion to produce the correct DM abundance and also generating observable gravitational wave signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Plausible constraints and inflationary production for dark photons

Generic constraints on dark photons are generally presented assuming they have Stueckelberg masses. These constraints are strengthened if instead the mass is due to the Higgs mechanism and the dark Higgs is light. First, we show that under reasonable assumptions on the origin of kinetic mixing 𝜀 and perturbativity, the strengthened constraints on 𝜀 cannot be arbitrarily relaxed by making the Higgs heavy. Second, we demonstrate a simple mechanism for generating dark photon dark matter after inflation, where fluctuations of a dark Higgs by stochastic misalignment can produce stable dark photons through ℎ →𝐴′⁢𝐴′ decay. Third, we point out new lower bounds on 𝜀 in the case where the dark photon mediates thermal freeze-out of light dark matter by 𝑠-channel exchange, taking account of generic expectations for the size of 𝜀, and astrophysical upper bounds on the self-interaction cross section.

inflation↗

Spin-Orbit-Induced Topological Flat Bands in Line and Split Graphs of Bipartite Lattices

Topological flat bands, such as the band in twisted bilayer graphene, are becoming a promising platform to study topics such as correlation physics, superconductivity, and transport. In this Letter, we introduce a generic approach to construct two-dimensional (2D) topological quasiflat bands from line graphs and split graphs of bipartite lattices. A line graph or split graph of a bipartite lattice exhibits a set of flat bands and a set of dispersive bands. The flat band connects to the dispersive bands through a degenerate state at some momentum. We find that, with spin-orbit coupling (SOC), the flat band becomes quasiflat and gapped from the dispersive bands. By studying a series of specific line graphs and split graphs of bipartite lattices, we find that (i) if the flat band (without SOC) has inversion or C 2 symmetry and is nondegenerate, then the resulting quasiflat band must be topologically nontrivial, and (ii) if the flat band (without SOC) is degenerate, then there exists a SOC potential such that the resulting quasiflat band is topologically nontrivial. This generic mechanism serves as a paradigm for finding topological quasiflat bands in 2D crystalline materials and metamaterials.

36 MATERIALS SCIENCE↗

Heavy Neutral Leptons via Axionlike Particles at Neutrino Facilities

Heavy neutral leptons (HNLs) are often among the hypothetical ingredients behind nonzero neutrino masses. If sufficiently light, they can be produced and detected in fixed-target-like experiments. We show that if the HNLs belong to a richer—but rather generic—dark sector, their production mechanism can deviate dramatically from expectations associated with the standard-model weak interactions. In more detail, we postulate that the dark sector contains an axionlike particle (ALP) that naturally decays into HNLs. Since ALPs mix with the pseudoscalar hadrons, the HNL flux might be predominantly associated with the production of neutral mesons (e.g., π 0 , η ) as opposed to charge hadrons (e.g., π ± , K ± ). In this case, the physics responsible for HNL production and decay are not directly related and experiments like DUNE might be sensitive to HNLs that are too weakly coupled to the standard model to be produced via weak interactions, as is generically the case of HNLs that play a direct role in the type-I seesaw mechanism. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Trends in spatial correlations, two-phase coexistence, and criticality in a class of type-2 Schloegl models for autocatalysis

A class of type-2 Schloegl models is considered for particles on a square lattice with variable-range cooperativity. These models involve: (i) spontaneous particle annihilation at rate p; (ii) autocatalytic particle creation at unoccupied sites (i, j) with n ⩾ 2 particles within a specified neighborhood, Ω 𝑁 (i, j), of sites at rate $k_n$ = $\frac{^{(^n_2)}}{_{(^N_2)}}$ = $\frac{n{(n-1)}}{_{N(N-1)}}$; and (iii) possible spontaneous particle creation at unoccupied sites at “small” rate ɛ ⩾ 0. In some cases, Ω 𝑁 just includes all symmetry-equivalent sites at a single specific distance 𝑑 (in units of lattice constants) from the unoccupied site, e.g., 𝑑 = 1 (nearest-neighbor sites) where 𝑁 = 4, or 𝑑 = √5 (or √13 or…) where 𝑁 = 8. In other cases, Ω 𝑁 includes sites multiple distances from the unoccupied site, e.g., 𝑑 = {1,√2}, where 𝑁 = 8. Kinetic Monte Carlo (KMC) simulation reveals that these models exhibit a nonequilibrium discontinuous phase transition between high- and low-density states below a critical point, ɛ < ɛ c , with generic two-phase coexistence (2PC) at least for smaller 𝑁. With some exceptions, there is an approach toward mean-field behavior with increasing 𝑁 (so the regime of generic 2PC shrinks, and ɛ c approaches the mean-field value of 1/27). Additional insight into trends is provided by analysis of the exact master equations for the models via hierarchical truncation. These truncations utilize suitably tailored pair approximations which reflect the dominant nonequilibrium spatial correlations. These correlations in turn are shown to reflect the details of the autocatalytic particle creation process. For spatially heterogeneous states, the truncations produce coupled sets of lattice differential equations (LDE) which can describe orientation-dependent propagation of an interface between high- and low-density steady states for ɛ < ɛ c . Pair approximation values of 𝑝 = 𝑝 eq where the interface is stationary, and its orientation-dependence, are in semiquantitative agreement with KMC results. In conclusion, this comparison accounts for propagation failure in the LDE which complicates interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models

The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.

artificial intelligence↗

Quantified Fast Frequency Response of Inverter-Based Resources for Bulk-Power System Study

Quantifying fast frequency response (FFR) of inverter-based resources (IBRs) is crucial for robust frequency regulation, managing resources, and improving system reliability in the power grids with high penetration levels of IBRs. This paper proposes a concept of frequency response scheme that its response is quantifiable and applicable to the generic IBR models. To achieve this, a stepwise-energy function is derived as a control module by considering operational constraints of IBRs. Then the module is implemented along with generic IBR models in electromagnetic transient (EMT) and electromechanical-based software. To quantify the FFR, the implemented module calculates available incremental active power for a specific time duration. This energy profile is being updated depending on IBR’s operating conditions and is provided into a power grid upon detecting a frequency event. Thus, due to this characteristic, this scheme can quantify the FFR and enable applicable IBRs to provide their available headroom within frequency arrest period. Thereby, this scheme can help estimate IBRs’ frequency response and is more effective in improving the initial frequency response than frequency-dependent control schemes: rate-of-change-of-frequency based and droop-based control schemes. The performance of the proposed scheme was tested under different IBR penetration levels using PSLF and PSCAD simulators.

Kim, Jinho↗

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM's existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

batteries↗

Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest

The unprecedented amount of scientific data has introduced heavy pressure on the current data storage and transmission systems. Progressive compression has been proposed to mitigate this problem, which offers data access with on-demand precision. However, existing approaches only consider precision control on primary data, leaving uncertainties on the quantities of interest (QoIs) derived from it. In this work, we present a progressive data retrieval framework with guaranteed error control on derivable QoIs. Our contributions are three-fold. (1) We carefully derive the theories to strictly control QoI errors during progressive retrieval. Our theory is generic and can be applied to any QoIs that can be composited by the basis of derivable QoIs proved in the paper. (2) We design and develop a generic progressive retrieval framework based on the proposed theories, and optimize it by exploring feasible progressive representations. (3) We evaluate our framework using five real-world datasets with a diverse set of QoIs. Experiments demonstrate that our framework can faithfully respect any user-specified QoI error bounds in the evaluated applications. This leads to over 2.02× performance gain in data transfer tasks compared to transferring the primary data while guaranteeing a QoI error that is less than 1E-5.

Wu, Xuan↗

Profiles of upcoming HPC Applications and their Impact on Reservation Strategies

With the expected convergence between HPC, BigData and AI, new applications with different profiles are coming to HPC infrastructures. Here, we aim at better understanding the features and needs of these applications in order to be able to run them efficiently on HPC platforms. The approach followed is bottom-up: we study thoroughly an emerging application from the neuroscience community (SLANT) to understand its behavior. Based on these observations, we derive a generic, yet simple, application model (namely, a linear sequence of stochastic jobs). We expect this model to be representative for a large set of upcoming applications that require the computational power of HPC clusters without fitting the typical behavior of large-scale traditional applications. In a second step, we show how one can manipulate this generic model in a scheduling framework. Specifically we consider the problem of making reservations (both time and memory) for an execution on an HPC platform. We derive solutions using the model of the first step of this work. We experimentally show the robustness of the model, even with very few data or with another application, to generate the model, and provide performance gains with regards to standard and more recent approaches used in the neuroscience community.

97 MATHEMATICS AND COMPUTING↗

Economic evaluation of the Hepatitis C virus elimination program in the country of Georgia, 2015 to 2017

Abstract Background and Aims In 2015, the country of Georgia launched an elimination program aiming to reduce the prevalence of Hepatitis C virus (HCV) infection by 90% from 5.4% prevalence (~150 000 people). During the first 2.5 years of the program, 770 832 people were screened, 48 575 were diagnosed with active HCV infection, and 41 483 patients were treated with direct‐acting antiviral (DAA)‐based regimens, with a >95% cure rate. Methods We modelled the incremental cost‐effectiveness ratio (ICER) of HCV screening, diagnosis and treatment between April 2015 and November 2017 compared to no treatment, in terms of cost per quality‐adjusted life year (QALY) gained in 2017 US dollars, with a 3% discount rate over 25 years. We compared the ICER to willingness‐to‐pay (WTP) thresholds of US$4357 (GDP) and US$871 (opportunity cost) per QALY gained. Results The average cost of screening, HCV viremia testing, and treatment per patient treated was $386 to the provider, $225 to the patient and $1042 for generic DAAs. At 3% discount, 0.57 QALYs were gained per patient treated. The ICER from the perspective of the provider including generic DAAs was $2285 per QALY gained, which is cost‐effective at the $4357 WTP threshold, while if patient costs are included, it is just above the threshold at $4398/QALY. All other scenarios examined in sensitivity analyses remain cost‐effective except for assuming a shorter time horizon to the end of 2025 or including the list price DAA cost. Reducing or excluding DAA costs reduced the ICER below the opportunity‐cost WTP threshold. Conclusions The Georgian HCV elimination program provides valuable evidence that national programs for scaling up HCV screening and treatment for achieving HCV elimination can be cost‐effective.

Tskhomelidze, Irina↗

Large-scale parametric modeling of spent nuclear fuel dynamics in the 30 cm package drop scenario

Packages used to transport spent nuclear fuel (SNF) are required by the U.S. Code of Federal Regulations 10 CFR 71.71 to demonstrate satisfactory performance during a drop scenario. While the CFR is meant to ensure safe package function, it does not evaluate survival of the SNF within. The U.S. Department of Energy Spent Fuel and Waste Science and Technology program is working on closing the knowledge gap related to the response of SNF to external mechanical loads, including the hypothetical 30 cm package drop scenario in the CFR. In support of this effort, LS-DYNA finite element simulations were developed by Pacific Northwest National Laboratory (PNNL) to model generic drop scenarios at both the package and fuel assembly level. The models were validated against one-third scale package and full scale fuel assembly drop test data and were exercised to predict fuel cladding strains in a narrow range of model configurations. This work describes a large-scale parametric study conducted by PNNL using the previously developed and validated PWR finite element model, with the addition of a new generic BWR assembly model. The motivation for the parametric study was to characterize the broad range of SNF responses in the 30 cm package drop scenario. This was accomplished by varying the drop orientation, fuel assembly type (17x17 PWR and 10x10 BWR), burnup, cladding temperature, spacer grid buckling load, package mass, impact limiter stiffness, and mechanical gap conditions within the basket. A MATLAB framework was developed to automate LS-DYNA model generation and execution on PNNL institutional computing resources. In total, over 2000 simulations were performed. For each simulation, the SNF response was quantified in terms of permanent grid deformation, fuel rod contact pressure, and strains within the fuel rods, guide tubes, and water rods. The results provide valuable insight into the range of responses that could be reasonably expected from SNF in the hypothetical drop scenario, as well as the sensitivity to each input parameter. The results of this parametric study are a key component of the testing and modeling strategy the Spent Fuel and Waste Science and Technology program is using to close the external loads knowledge gap.

Kadooka, Kevin↗

Data preservation in high energy physics

Data preservation is a mandatory specification for any present and future experimental facility and it is a cost-effective way of doing fundamental research by exploiting unique data sets in the light of the continuously increasing theoretical understanding. This document summarizes the status of data preservation in high energy physics. The paradigms and the methodological advances are discussed from a perspective of more than ten years of experience with a structured effort at international level. The status and the scientific return related to the preservation of data accumulated at large collider experiments are presented, together with an account of ongoing efforts to ensure long-term analysis capabilities for ongoing and future experiments. Transverse projects aimed at generic solutions, most of which are specifically inspired by open science and FAIR principles, are presented as well. A prospective and an action plan are also indicated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New procedure for evaluation of U(3) coupling and recoupling coefficients

A simple method to calculate Wigner coupling coefficients and Racah recoupling coefficients for U(3) in two group–subgroup chains is presented. While the canonical U(3) coupling and recoupling coefficients are applicable to any system that respects U(3) symmetry, the U(3) coupling coefficients are more specific to nuclear structure studies. This new procedure precludes the use of binomial coefficients and alternating sums which were used in the 1973 formulation of Draayer and Akiyama, and in so doing provides a faster and more accurate determination of any and all required results. The resolution of the outer multiplicity is based on the null space concept of the U(3) generators proposed by Alex et al., whereas the inner multiplicity in the angular momentum subgroup chain is obtained from the dimension of the null space of the SO(3) raising operator. It is anticipated that a C++ library will ultimately be available for determining generic coupling and recoupling coefficients associated with both the canonical and the physical group–subgroup chains of U(3).

Cross-Coupling Reaction↗

SoS-SDQN: System of Systems Software-defined Quantum Networking

Quantum networks are needed for quantum domain applications that may run across different network deployments - point-to-point, multi-node networks, and possibly across inter-domain quantum networks, like the quantum internet. Unlike classical computing networks, quantum networks involve heterogeneous systems nodes that currently require local and manual control. This needs a unified control approach to help them integrate, work seamlessly, and have global knowledge. Software-defined Networking (SDN) has been successfully leveraged in classical networking for seamless and software-driven control of network infrastructure and packet switching, but not in management of quantum network applications across heterogeneous systems. In this paper, we review the current state of the art and present early developments of a System-of-Systems Software-defined Quantum Networking architecture (SoS-SDQN), a generic architecture that supports software-driven quantum network experiments across heterogeneous quantum systems. The architecture modifies the generic SDN to address the domain requirements of quantum networks and proposes a multilevel SDQN to provide a global view of network status, running applications, and control of incorporated heterogeneous quantum systems. We also design and implement a SoS SouthBound Quantum Interface (SoS-SBQI), a quantum infrastructure protocol that abstracts automation of applications across the network.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗

Wrapper for the optimization of cross-section generation in OpenMC

The "Wrapper for the optimization of cross-section generation in OpenMC" is Python-based software that runs the open-source Monte Carlo code OpenMC (https://docs.openmc.org/en/stable/ ) to generate cross-sections for any reactor geometry. The wrapper then optimizes those cross sections. The optimization aims to choose an energy group structure and a scattering representation that maximize accuracy with respect to continuous-energy results while avoiding significant computational expense. It then outputs these cross-sections in an ISOXML format readable by the Idaho National Lab code suite MOOSE (Olin William Calvin, Mark D DeHart, “Architecture for the Performance of Nuclear Fuel Depletion Calculations”, Idaho National Laboratory report, November 2019). The expected use-cases of this software include: -finding the best group structure and scattering representation for a specific reactor -testing the appropriateness of energy group structures for different reactor types -comparing energy group structures and scattering representations to each other -generating cross sections for use in deterministic codes, including ones found in the MOOSE suite The example reactor geometry included in this release is a generic reactor design, not based on any reactor in existence or in development. It was fabricated for the sole purpose of being a “testbed-geometry” upon which to develop this tool. Since the tool is designed to be generic, the nature of the test geometry is not very important, however, it is valuable to include as an example for users who are unfamiliar with developing reactor geometries for OpenMC.

Kreher, Miriam↗

CHMMPP: A c++ library for constrained Hidden Markov Models

SAND2024-13027O The CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.

Hart, William↗